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arXiv Machine Learning By Piyush Saha, Evan Newell, Hanna O'Leary, Arun Natarajan, Alireza Aghasi

K-TRAIL: Simulator-Guided Generative Design of EM/RF Circuits

Read the original on arXiv Machine Learning →

K-TRAIL is a simulator-guided generative framework that uses diffusion-based layout generation combined with derivative-free ensemble Kalman guidance to design RF and electromagnetic circuits. It allows a black-box EM simulator to refine candidate layouts during generation, supporting synthesis from target S-parameter responses or direct RF performance constraints. Experiments on multi-layer RFIC structures demonstrate improved agreement with target responses and the ability to discover structurally distinct layouts that meet design requirements.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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